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view.py: use a different colormap for sea, to distinguish it from lakes

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Gael-de-Sailly 2021-09-07 12:00:47 +02:00
parent 27670addb3
commit b246cb775b
1 changed files with 23 additions and 6 deletions
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29
view.py
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@ -11,10 +11,12 @@ try:
import colorcet as cc import colorcet as cc
cmap1 = cc.cm.CET_L11 cmap1 = cc.cm.CET_L11
cmap2 = cc.cm.CET_L12 cmap2 = cc.cm.CET_L12
cmap3 = cc.cm.CET_L6.reversed()
except ImportError: # No module colorcet except ImportError: # No module colorcet
import matplotlib.cm as cm import matplotlib.cm as cm
cmap1 = cm.summer cmap1 = cm.summer
cmap2 = cm.Blues cmap2 = cm.ocean.reversed()
cmap3 = cm.Blues
except ImportError: # No module matplotlib except ImportError: # No module matplotlib
has_matplotlib = False has_matplotlib = False
@ -24,10 +26,12 @@ if has_matplotlib:
water = np.maximum(lakes_sea - dem, 0) water = np.maximum(lakes_sea - dem, 0)
max_elev = dem.max() max_elev = dem.max()
max_depth = water.max() max_depth = water.max()
max_lake_depth = lakes.max()
ls = mcl.LightSource(azdeg=315, altdeg=45) ls = mcl.LightSource(azdeg=315, altdeg=45)
norm_ground = plt.Normalize(vmin=sea_level, vmax=max_elev) norm_ground = plt.Normalize(vmin=sea_level, vmax=max_elev)
norm_sea = plt.Normalize(vmin=0, vmax=max_depth) norm_sea = plt.Normalize(vmin=0, vmax=max_depth)
norm_lake = plt.Normalize(vmin=0, vmax=max_lake_depth)
rgb = ls.shade(dem, cmap=cmap1, vert_exag=1/scale, blend_mode='soft', norm=norm_ground) rgb = ls.shade(dem, cmap=cmap1, vert_exag=1/scale, blend_mode='soft', norm=norm_ground)
(X, Y) = dem.shape (X, Y) = dem.shape
@ -37,13 +41,23 @@ if has_matplotlib:
extent = (-0.5*scale, (Y-0.5)*scale, -0.5*scale, (X-0.5)*scale) extent = (-0.5*scale, (Y-0.5)*scale, -0.5*scale, (X-0.5)*scale)
plt.imshow(np.flipud(rgb), extent=extent, interpolation='antialiased') plt.imshow(np.flipud(rgb), extent=extent, interpolation='antialiased')
alpha = (water > 0).astype('u1') alpha = (water > 0).astype('u1')
plt.imshow(np.flipud(water), alpha=np.flipud(alpha), cmap=cmap2, extent=extent, vmin=0, vmax=max_depth, interpolation='antialiased') lakes_alpha = ((lakes_sea - np.maximum(dem,sea_level)) > 0).astype('u1')
# plt.imshow(np.flipud(water), alpha=np.flipud(alpha), cmap=cmap2, extent=extent, vmin=0, vmax=max_depth, interpolation='antialiased')
plt.imshow(np.flipud(water), alpha=np.flipud(alpha), cmap=cmap3, extent=extent, vmin=0, vmax=max_depth, interpolation='antialiased')
plt.imshow(np.flipud(water), alpha=np.flipud(lakes_alpha), cmap=cmap2, extent=extent, vmin=0, vmax=max_depth, interpolation='antialiased')
sm1 = plt.cm.ScalarMappable(cmap=cmap1, norm=norm_ground) sm1 = plt.cm.ScalarMappable(cmap=cmap1, norm=norm_ground)
plt.colorbar(sm1).set_label('Elevation') plt.colorbar(sm1).set_label('Elevation')
sm2 = plt.cm.ScalarMappable(cmap=cmap2, norm=norm_sea) sm2 = plt.cm.ScalarMappable(cmap=cmap2, norm=norm_lake)
plt.colorbar(sm2).set_label('Water depth') cb2 = plt.colorbar(sm2)
cb2.ax.invert_yaxis()
cb2.set_label('Lake Depth')
sm3 = plt.cm.ScalarMappable(cmap=cmap3, norm=norm_sea)
cb3 = plt.colorbar(sm3)
cb3.ax.invert_yaxis()
cb3.set_label('Ocean Depth')
plt.xlabel('X') plt.xlabel('X')
plt.ylabel('Z') plt.ylabel('Z')
@ -84,9 +98,10 @@ def stats(dem, lakes, scale=1):
lake_surface = lake.sum() lake_surface = lake.sum()
print('--- General ---') print('--- General ---')
print('Grid size: {:5d}x{:5d}'.format(dem.shape[0], dem.shape[1])) print('Grid size (dem): {:5d}x{:5d}'.format(dem.shape[0], dem.shape[1]))
print('Grid size (lakes): {:5d}x{:5d}'.format(lakes.shape[0], lakes.shape[1]))
if scale > 1: if scale > 1:
print('Map size: {:5d}x{:5d}'.format(int(dem.shape[0]*scale), int(dem.shape[1]*scale))) print('Map size: {:5d}x{:5d}'.format(int(dem.shape[0]*scale), int(dem.shape[1]*scale)))
print() print()
print('--- Surfaces ---') print('--- Surfaces ---')
print('Continents: {:6.2%}'.format(continent_surface/surface)) print('Continents: {:6.2%}'.format(continent_surface/surface))
@ -100,3 +115,5 @@ def stats(dem, lakes, scale=1):
print('Mean continent elev: {:4.0f}'.format((dem*continent).sum()/continent_surface)) print('Mean continent elev: {:4.0f}'.format((dem*continent).sum()/continent_surface))
print('Lowest elevation: {:4.0f}'.format(dem.min())) print('Lowest elevation: {:4.0f}'.format(dem.min()))
print('Highest elevation: {:4.0f}'.format(dem.max())) print('Highest elevation: {:4.0f}'.format(dem.max()))
print()